Strengthening Enterprise Risk Management Strategies, Addressing AI-Related Risks in the Corporate and Business Ecosystems

The digital world has changed tremendously in the last three decades, and digital natives and digital product developers have been key factors in these changes. The proliferation, availability, and use of digital tools are dependent on users and the use cases these tools are designed for. As the digital ecosystem continues to expand, giving room to the execution of hitherto impossible and, most often, unimaginable tasks, Artificial Intelligence (AI) has expanded the limits of opportunities and possibilities within the digital sphere.

Globally, Artificial Intelligence (AI) has been shaping and reshaping industries and unlocking unprecedented opportunities, allowing individuals and institutions to expand their creative horizons. While the evolution of AI has been an interesting one, it has equally brought with it, new and complex risks that organizations must be aware of.

As an Enterprise Risk Manager, have you taken the time to evaluate these new realities? As a CRM in an organization, have you charted a new course and a new governance structure to proactively mitigate AI-related risks to ensure that while your organization fully optimizes the advantages of AI adoption, it is safeguarded against unintended consequences?

As the corporate world continues to experience a surge in the usage and optimization of AI-powered tools and systems, forward-thinking organizations have taken steps toward a deeper understanding of the inherent risks related to AI while designing mitigating systems around those risks.

1. Conduct Comprehensive Risk Assessments

As an Enterprise Risk Manager tasked with leading an organization’s enterprise-grade infrastructure and processes, a first, safe line of action in the wide optimization of AI is to ensure the appropriate evaluation and assessment of potential risks, including vulnerabilities, reputational considerations, impact on workforce culture and regulatory compliance. ?It is pivotal to incorporate ethical considerations into AI use and optimization in any organization, especially when such tools are central to decision-making in such an organization.

2. Development of a Robust Governance Framework

Forward-thinking institutions are known to avoid diving head-first into new technological revolutions. As an organization looking to utilize enterprise-grade Artificial Intelligence, there is a need to consider some quality internal groundwork, including organizational alignment to AI infrastructure, workforce culture and expertise as well as policy development and the development of a governance structure that supports the safe use of AI. Ticking the boxes on these first lines of action ensures the safety of the organization and prevents misuse or mismanagement of these novel tools.

3. Management of third-party AI risks

With the proliferation of AI tools, there has been an increase in the design and development of AI-powered third-party tools. Developers have perfected the design of enterprise-grade digital tools to serve multiple purposes across an organization. This is why it is pivotal for organizations also to address risks that stem from the utilization of such tools while setting boundaries in the incorporation of these tools into existing risk management strategies.

4. Investment in Workforce Upskill

Novel technologies create opportunities for organizations to close the skills gap and empower their workforce with the requisite knowledge, technical skills and creative expertise to navigate new realities. Organizations must assess and understand these skills gaps and the limitations of their workforce to not only optimize these technologies but also to mitigate any risks associated with the use of these technologies.

5. Prioritization of Data Privacy and Integrity

Data is the new oil. The value of data in small and large organizations cannot be overemphasized. Forward-thinking organizations have maintained a sustainable culture of investing in data protection while ensuring the security of information and investments. It is in no way a coincidence that AI thrives on data. Organizations must therefore expend resources and give priority to the Implementation of airtight data governance practices. This will prevent data breaches, and human errors and ensure compliance with privacy regulations.